about 2 hours ago
Responsibilities
- Build and ship core product ML capabilities, including optimization and recommendation engines.
- Own the full model lifecycle from EDA to production deployment and monitoring.
- Build and scale data pipelines and serving architectures using modern tools.
- Collaborate with Backend and Platform teams to enhance feature serving and data architecture.
- Mentor engineers and help set the technical direction for ML at Iterable.
Requirements
- 5+ years of hands-on experience in machine learning engineering.
- Mastery of Databricks and Spark for building and optimizing data pipelines.
- Proven track record of deploying deep learning and ensemble models in production.
- Strong programming skills in Python and/or Scala with a focus on maintainable code.
- Experience with microservices, distributed computing, and containerization.
Benefits
- Competitive salaries and meaningful equity.
- Private Medical Insurance.
- Life/Risk Assurance.
- Meal Allowance of 8.55€ per day.
- Community Days for giving back.
- 22 days of Paid Annual Leave.
- Global Lifestyle Reimbursement Account.
- Paid Sabbatical.
- Complete laptop workstation.
Tech Stack
Categories
AI & MLData Engineering